def test_model_graph():
t1 = Table("t1", [
Column("c1", int, None, True, False, None),
Column("c2", int, None, False, False, None),
])
t2 = Table("t2", [
Column("c1", int, None, True, False, None),
Column("c2", int, None, False, False, None),
])
m1 = define_model(t1, [CRUDMixin, GraphEntityMixin])
m2 = define_model(t2, [CRUDMixin, GraphEntityMixin])
t = graph_template(
m1 = m1,
m2 = m2,
)
t.m2 >> t.m1
graph = Graph(t)
graph.append(
m1 = m1(c1 = 1, c2 = "a"),
m2 = m2(c1 = 1, c2 = 1),
)
graph.append(
m1 = m1(c1 = 2, c2 = "b"),
m2 = m2(c1 = 2, c2 = 2),
)
graph.append(
m1 = m1(c1 = 2, c2 = "dummy"),
m2 = m2(c1 = 3, c2 = 2),
)
graph.append(
m1 = m1(c1 = None, c2 = None),
m2 = m2(c1 = 3, c2 = 2),
)
graph.append(
m1 = m1(c1 = 3, c2 = "c"),
m2 = m2(c1 = 1, c2 = 3),
)
graph.append(
m1 = m1(c1 = 4, c2 = "d"),
m2 = m2(c1 = None, c2 = None),
)
assert graph_dict(
graph.view,
m1 = (),
m2 = (),
) == dict(
m1 = [
dict(c1 = 1, c2 = "a", m2 = [dict(c1 = 1, c2 = 1)]),
dict(c1 = 2, c2 = "b", m2 = [dict(c1 = 2, c2 = 2), dict(c1 = 3, c2 = 2)]),
dict(c1 = 3, c2 = "c", m2 = [dict(c1 = 1, c2 = 3)]),
dict(c1 = 4, c2 = "d", m2 = []),
]
)
def test_no_pk():
t1 = Table("t1", [
Column("c1", int, None, False, False, None),
Column("c2", int, None, False, False, None),
])
m1 = define_model(t1, [CRUDMixin, GraphEntityMixin])
t = graph_template(m1 = m1)
graph = Graph(t)
graph.append(m1 = m1(c1 = 1, c2 = "a"))
graph.append(m1 = m1(c1 = 1, c2 = "a"))
assert len(graph.view.m1) == 2
def test_add_serializer():
t1 = Table("t1", [
Column("c1", int, None, True, False, None),
Column("c2", int, None, False, False, None),
])
m1 = define_model(t1, [CRUDMixin, GraphEntityMixin])
t = graph_template(m1 = m1)
graph = Graph(t)
graph.append(m1 = m1(c1 = 1, c2 = "a"))
add_serializer(m1, lambda s, x: dict(c1 = x.c1 * 2, c2 = f"__{x.c2}__"))
assert graph_dict(graph.view, m1 = ()) == dict(m1 = [dict(c1 = 2, c2 = "__a__")])
def test_add_identifier():
t1 = Table("t1", [
Column("c1", int, None, True, False, None),
Column("c2", int, None, False, False, None),
])
m1 = define_model(t1, [CRUDMixin, GraphEntityMixin])
add_identifier(m1, lambda x: x.c2)
t = graph_template(m1 = m1)
graph = Graph(t)
graph.append(m1 = m1(c1 = 1, c2 = "a"))
graph.append(m1 = m1(c1 = 2, c2 = "a"))
assert len(graph.view.m1) == 1
v = graph.view.m1[0]()
assert v.c1 == 1
assert v.c2 == "a"
def test_add_entity_filter():
t1 = Table("t1", [
Column("c1", int, None, True, False, None),
Column("c2", int, None, False, False, None),
])
m1 = define_model(t1, [CRUDMixin, GraphEntityMixin])
add_entity_filter(m1, lambda x: x.c1 >= 0)
t = graph_template(m1 = m1, v = int)
t.m1 << t.v
graph = Graph(t)
graph.append(m1 = m1(c1 = -1, c2 = "a"), v = 1)
graph.append(m1 = m1(c1 = 0, c2 = "b"), v = 2)
graph.append(m1 = m1(c1 = 1, c2 = "c"), v = 3)
assert [(n().c1, n().c2) for n in graph.view.m1] == [(0, "b"), (1, "c")]
assert [n() for n in graph.view.v] == [2, 3]
assert [n() for n in graph.view.m1[0].v] == [2]
assert [n() for n in graph.view.m1[1].v] == [3]
for i in range(0, 20):
blog_category.inserts(
db,
[dict(
blog_id=i + 1,
name=f"category_{i}_{j}",
) for j in range(0, 3)])
# Declare template representing graph structure.
t = graph_template(
blogs=blog,
recent_posts=post,
total_posts=int,
categories=blog_category,
images=image,
recent_comments=post_comment,
most_liked_comment=post_comment,
total_comments=int,
total=int,
)
t.blogs << [t.categories, t.total_posts, t.recent_posts]
t.recent_posts << [
t.images, t.recent_comments, t.most_liked_comment, t.total_comments
]
def fetch_blogs():
# Create graph instance.
graph = new_graph(t)